title: Optimal goodness-of-fit tests for recurrent event data.
abstract: A class of tests for the hypothesis that the baseline intensity belongs to a parametric class of intensities is given in the recurrent event setting. Asymptotic properties of a weighted general class of processes that compare the non-parametric versus parametric estimators for the cumulative intensity are presented. These results are given for a sequence of Pitman alternatives. Test statistics are proposed and methods of obtaining critical values are examined. Optimal choices for the weight function are given for a class of chi-squared tests. Based on Khmaladze's transformation we propose distributional free tests. These include the types of Kolmogorov-Smirnov and Cramér-von Mises. The tests are used to analyze two different data sets.
authors.affiliation: Department of Mathematics, Indiana University of Pennsylvania, Indiana, PA 15705, USA. rstocker@iup.edu
authors.forename: Russell S
authors.initials: RS
authors.lastname: Stocker
authors.forename: Akim
authors.initials: A
authors.lastname: Adekpedjou
mesh_terms: D000389:Air Conditioning / Q000295:instrumentation; D016009:Chi-Square Distribution; D003627:Data Interpretation, Statistical; D015233:Models, Statistical; D013269:Stochastic Processes